로컬 지식 베이스에 대한 시맨틱 검색을 제공하여 AI 클라이언트가 컨텍스트 창을 소모하지 않고도 관련 문서 구절을 찾을 수 있도록 합니다.
다른 이름 VBlackJack/Cortex, cortex-local-rag
- 스타
- 1
- Tools
- 4
- 다운로드, 30일
- 2,443
- 최신 버전
- 2026.1021.3
- 마지막 커밋
- 2026년 10월 21일
- 라이선스
- Apache-2.0
Cortex MCP란?
Cortex은(는) MCP server입니다. 로컬 지식 베이스에 대한 시맨틱 검색을 제공하여 AI 클라이언트가 컨텍스트 창을 소모하지 않고도 관련 문서 구절을 찾을 수 있도록 합니다. 4개 도구를 제공합니다. 예: cortex_search, cortex_sync, cortex_list_sections.
프로젝트 README에서 생성된 요약
Cortex MCP server 정보
Cortex는 로컬 지식 베이스에 대한 시맨틱 검색 기능을 제공하여 Claude, Gemini, Cursor와 같은 AI 클라이언트가 컨텍스트 창을 낭비하지 않고도 관련 문서 구절을 검색할 수 있게 합니다. 문서를 로컬에서 처리하고 인덱싱하는 MCP server로 작동하므로 콘텐츠가 사용자의 기기에 안전하게 유지됩니다. 이 시스템은 paraphrase-multilingual-MiniLM-L12-v2 모델을 사용한 다국어 벡터 검색을 통해 영어와 프랑스어를 지원합니다.
사용자는 Cortex Companion 인터페이스 또는 CLI를 통해 데이터를 관리할 수 있습니다. 이 서버는 Markdown 및 PDF를 포함한 다양한 문서 형식을 지원하며, 허용 목록에 있는 공간을 가져올 수 있는 선택 사항인 Confluence writer를 제공합니다. 개발자는 전체 폴더를 인덱싱하거나 특정 이름의 섹션을 인덱싱하는 방식 중 선택할 수 있습니다. 설정은 별도의 Python 또는 .NET 런타임이 필요 없는 통합 Windows 설치 프로그램을 통해 제공되거나, macOS 및 Linux용 단독 아카이브를 통해 제공됩니다.
활용 사례
- 1시맨틱 문서 검색의미 기반 검색을 사용하여 로컬 PDF 또는 Markdown 파일 내에서 특정 정보를 찾도록 AI 클라이언트에 요청합니다.
- 2Confluence 지식 통합특정 Confluence 공간을 로컬 지식 베이스와 동기화하여 AI 지원 쿼리를 수행합니다.
- 3정리된 섹션 기반 검색AI의 검색 범위를 프로젝트나 노트와 같은 특정 하위 폴더로 제한하여 검색 결과의 관련성을 높입니다.
프로젝트의 README를 바탕으로 작성되었습니다. 모든 활용 사례는 해당 내용의 인용문과 대조하여 확인합니다.
Cortex MCP 설치 방법
형식 확인: 2026년 11월 10일Claude Code에 Cortex MCP 설치
$ claude mcp add --env CORTEX_KB_PATH=<CORTEX_KB_PATH> cortex -- uvx cortex-local-ragCursor에 Cortex MCP 설치
~/.cursor/mcp.json
{
"mcpServers": {
"cortex": {
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}VS Code에 Cortex MCP 설치
.vscode/mcp.json
{
"servers": {
"cortex": {
"type": "stdio",
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Claude Desktop에 Cortex MCP 설치
claude_desktop_config.json
{
"mcpServers": {
"cortex": {
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Codex에 Cortex MCP 설치
~/.codex/config.toml
[mcp_servers.cortex] command = "uvx" args = ["cortex-local-rag"] [mcp_servers.cortex.env] CORTEX_KB_PATH = "<CORTEX_KB_PATH>"
Gemini CLI에 Cortex MCP 설치
~/.gemini/settings.json
{
"mcpServers": {
"cortex": {
"command": "uvx",
"args": [
"cortex-local-rag"
],
"env": {
"CORTEX_KB_PATH": "<CORTEX_KB_PATH>"
}
}
}
}Cortex MCP 도구 4
README에서 감지됨cortex_searchcortex_synccortex_list_sectionscortex_freshness
| cortex_search | — | |
| cortex_sync | — | |
| cortex_list_sections | — | |
| cortex_freshness | — |
구성
CORTEX_KB_PATH필수Absolute path to the local knowledge base Cortex indexes and serves.
| 이름 | 설명 | 유형 |
|---|---|---|
| CORTEX_KB_PATH | Absolute path to the local knowledge base Cortex indexes and serves. | 필수 |
자동 검사
2026년 11월 12일에 실행됨전체 보고서 →자동 검사를 통과했습니다. 이는 보안 감사가 아닙니다. 코드를 직접 읽고 서버에 필요한 최소한의 권한만 부여하십시오. 검사 방식
- 소스 저장소 연결 및 접근 가능통과
- 오픈 소스 라이선스 (OSI)통과
- 최근 1년 내 커밋 또는 릴리스통과
- 패키지 이름이 인기 패키지와 유사하지 않음통과
- 원격 엔드포인트가 HTTPS 사용검사되지 않음
- 파괴적인 도구에 라벨 표시됨통과
- 모델에 대한 숨겨진 지침 없음통과
- 패키지와 의존성에 심각한 보안 권고 없음통과
README
GitHub에서 보기Cortex - RAG MCP for a knowledge base
English | Français
Cortex is an MCP (Model Context Protocol) server that exposes semantic search over a local knowledge base. It lets Claude, Codex and Gemini find the right passage in your documents without wasting their context window. Search is semantic (by meaning, not keyword), in French and in English. Cortex processes and indexes the knowledge base locally without sending its content; the MCP client may still pass requested chunks to its model under its own policy. The optional Confluence writer only downloads explicitly allowlisted spaces; the generated Markdown, vector index, and lexical index remain local.
Starting with 2026.0906.01, Companion offers a guided home screen, operation history and Confluence setup from one page or space link. Connection and measured scope confirmation stay in the flow; successful collection is followed by indexing. Use the combined installer to keep Cortex and Companion compatible.
Since 2026.0909.02, Confluence updates preserve the served generation when subtree enumeration fails and apply changed target/classification settings on retry. Search uses multilingual vector retrieval by default; CLI and MCP callers can explicitly select hybrid or reranked search. The first successful collection after upgrading regenerates older publication revisions, and the following sync removes obsolete index entries.
Guided document updates (2026.0909.00)
Companion brings local documents and Confluence together in My sources, with one Update my documents action. Search previews are resizable, large page trees render visible rows, and cancelling review preparation keeps the draft. Readiness now follows the saved document folder and configuration, including after restart. Run one document update after upgrading to establish this evidence for older indexes. See the release notes.
Measured scope without enumerating the space (2026.0907.00)
Adding a Confluence source measures its page, subtree and whole-space scopes with one indexed count each instead of reading the space page by page. On a 5916-page space that measurement took 3 min 19 s, past the timeout of every graphical caller, so Companion showed nothing at all. It now answers in about a second, and the emitted contract is unchanged.
Two whole-space numbers shift by one as a result: the resolved page is no longer folded into the space total, and a space with no visible page reports zero rather than one. A deployment whose search endpoint returns no total cannot measure a scope and reports that as a permanent failure instead of a retryable one. See the contracts.
Paired Companion 2026.0907.00 restores the contrast of the scope window, whose options were drawn in the system text colour, and stops reporting a timeout as a connection failure or advising a delay increase that silently reverts.
Source management in Companion (2026.0906.02)
The workflow includes search, remote page trees, impact review, evidence-based readiness, save-and-update, last-removal undo and recovery actions. See the contracts.
Paired version 2026.0906.02 provides visible My sources cards, a prefilled selection editor, confirmed page/space removal and browser links to originals. Removal only changes Cortex tracking; search reflects it after successful collection and indexing.
Removing the final source explicitly writes spaces = [] in a schema v2 or v3
configuration. This intentional empty allowlist permits an empty publication
with tombstones for prior documents. An absent spaces key remains incomplete
configuration and collection is refused. Connection and credential validation
and publication safeguards still apply. Both updated components are required;
this capability is absent from the installed 2026.0906.01 release.
Installation
Windows, no Python (recommended)
The simplest path: one installer for Cortex, Cortex Companion, the windowless Confluence converter, and the offline models. No separate Python or .NET runtime is required.
- Download
Cortex-Setup.exeandSHA256SUMSfrom the latest release. - Before running the unsigned installer, calculate its digest with
Get-FileHash .\Cortex-Setup.exe -Algorithm SHA256in PowerShell and verify that it exactly matches theCortex-Setup.exeline inSHA256SUMS. - Double-click only after that check. If SmartScreen still warns, select
More info, thenRun anyway. - Choose the folder that holds your documents, keep
Index everything in this folder, and finish. Cortex Companion opens when installation completes. Indexing only starts when you request synchronization in Companion. - In Companion, open
Settingsand verify the knowledge-base folder. The Cortex executable installed with Companion is detected automatically. - Drop your documents in that folder, open
Local database, then selectSynchronize local documents. - Restart your AI application: Cortex shows up there as an MCP server.
Companion then lets you synchronize, schedule, diagnose, and configure Cortex without a terminal. Details, silent mode and reinstall: Windows install.
Standalone archives (Windows x64, macOS Apple Silicon, Linux x64)
Every release also ships one ZIP archive per platform. It unpacks to a cortex/
folder holding the cortex or cortex.exe executable (MCP server + CLI, no
Python), its runtime, and the licenses for every embedded dependency; keep the
folder whole. See Standalone distribution.
From PyPI (Python, advanced)
py -m pip install --upgrade cortex-local-rag
cortex setup
This path installs the CLI and MCP server, but not Cortex Companion. The model is downloaded on first use if its cache is empty.
From source (development)
:: From the folder where you cloned Cortex
install.bat
install.bat and sync.bat are the development path for a source checkout,
not a supported end-user installation: install.bat installs the unlocked
dependencies from requirements.txt, and sync.bat indexes the folder section
by section without the Confluence documents. To use Cortex, install
Cortex-Setup.exe or a standalone archive instead. Details:
Setup.
How it works
Documents folder (.md, .pdf) Optional Confluence writer (REST)
| |
| current Markdown generation
+------------------+-------------------+
|
v
cortex sync <- Split, hash, vectorize, update FTS5
|
v
%LOCALAPPDATA%\Cortex\ <- ChromaDB + lexical.db
|
v
cortex serve <- MCP server (FastMCP)
|
v
MCP clients <- Claude / Codex / Gemini / Antigravity / LM Studio / Cursor / Windsurf / VS Code
The embedding model is the multilingual ONNX
paraphrase-multilingual-MiniLM-L12-v2. The Windows installer bundles it; a
source installation or standalone binary downloads it when the local cache is
empty.
Two indexing modes
- Whole folder (default): anything you place in the chosen folder, at the root or in any subfolder, becomes searchable. Nothing to configure.
- Sections (advanced): limits indexing to named subfolders you can search
separately (defaults
knowledge,projects,notes).
These modes govern the user-selected document folder. Generated ingestion
documents are indexed separately from the current published generation with
source_kind=doc and section sources.
Details: Configuration.
The cortex command
The installed package exposes a single command:
| Subcommand | Purpose |
|---|---|
cortex setup |
Config + index + client registration in one go (--kb-path, --yes, --no-index, --reset). |
cortex serve |
Runs the MCP server (used by clients). |
cortex sync |
Incremental index synchronization. |
cortex search |
Searches the index from the console (debugging aid). |
cortex ingestion |
Shows source health and whether catch-up is due. |
cortex confluence |
Stores the PAT interactively or runs the allowlisted writer. |
cortex config |
Reads or changes configuration through an atomic JSON contract, notably for Companion. |
cortex daemon |
Runs, inspects or stops the shared per-user server used when [server] mode = "shared" (opt-in). |
cortex bundle |
Describes or verifies an encrypted portable archive. |
cortex doctor |
Installation diagnostics (read-only). |
cortex register / cortex unregister |
Adds or removes Cortex from MCP clients. |
cortex init |
Creates the single per-user configuration. |
cortex check |
Verifies the installation. |
cortex --help describes every subcommand and cortex <command> --help describes
its options. A prompt-free installation scripts as:
cortex setup --yes --kb-path "D:\Documents\Knowledge"
Exposed MCP tools
| Tool | Description |
|---|---|
cortex_search |
Multilingual vector search by default; optional retrieval_mode (vector, hybrid, rerank). Parameters: query, section, top_k (1-10), source/author filters, and occurred/updated date ranges. |
cortex_sync |
Triggers an incremental sync of the selected folder and, on a full sync, the current published document generation. |
cortex_list_sections |
Lists included sections and "out of policy" folders. |
cortex_freshness |
Read-only vault and ingestion freshness summary. Parameters: section (optional), include_entries (false by default). |
Documentation
- Table of contents
- Windows install: unified Cortex + Companion + Confluence converter + models installer, corpus choice, silent mode, reinstall.
- Standalone distribution: per-platform archives and reproducible builds.
- Install from source: prerequisites, MCP clients.
- User guide: sync, search, tools, doctor, logs.
- FAQ: installation, local data, sync, and diagnostics.
- Release notes: user-visible changes by version and the published-history notice.
- Technical changelog: complete changes by version.
- Configuration:
config.toml, indexing modes, sections, data home, migration. - Ingestion scheduling: source health, catch-up, retries, and Task Scheduler.
- Metadata v2 migration: structured search metadata, backup, migration, and restore.
- Confluence writer: allowlisted REST ingestion, Windows Credential Manager, conversion, and atomic generations.
- Reproducible install:
requirements.lock,--require-hashes, regenerating the lock. - Public specification: MCP surface, index contracts, data, distribution, and limits.
- Architecture: end-to-end and technical choices.
- Security: local runtime, telemetry off, single-writer.
Prerequisites
| Path | Requirements |
|---|---|
| Windows installer | No separate Python or .NET runtime. At least ~500 MB of space (applications, model + index). |
| Standalone archive | No Python. ~500 MB of space (model + index). |
| From source | Python 3.11 to 3.13. ~500 MB of space. |
| Client | Claude Desktop/Code, Codex, Gemini, Antigravity, LM Studio, Cursor, Windsurf or VS Code (MCP support). |
License
Apache 2.0. See LICENSE.
Retrieval validation
See the validation guide for the desktop JSON search contract, the isolated FR/EN relevance corpus, performance measurements and exact paired-commit checks.
Cortex MCP 질문
Cortex MCP를 Claude Code에 추가하려면 어떻게 하나요?
터미널에서 claude mcp add --env CORTEX_KB_PATH=<CORTEX_KB_PATH> cortex -- uvx cortex-local-rag를 실행합니다. 모든 프로젝트에서 사용할 수 있게 하려면 --scope user를 추가합니다.
Cortex MCP를 Cursor에 추가하려면 어떻게 하나요?
~/.cursor/mcp.json를 열고 mcpServers 아래에 서버를 추가합니다. 위 설치 섹션에 표시된 Cursor 구성을 사용합니다.
Cortex MCP는 어떤 도구를 제공하나요?
4개 도구를 제공합니다. 예: cortex_search, cortex_sync, cortex_list_sections, cortex_freshness.
Cortex가 문서 내용을 클라우드로 전송하나요?
아니요, Cortex는 콘텐츠를 전송하지 않고 로컬에서 지식 베이스를 처리하고 인덱싱합니다.
시맨틱 검색은 어떤 언어를 지원하나요?
프랑스어와 영어를 모두 지원하는 다국어 검색이 가능합니다.
Confluence와 함께 Cortex를 사용할 수 있나요?
네, 명시적으로 허용 목록에 추가된 공간을 다운로드하는 선택 사항인 Confluence writer가 있습니다.